CUB [1]} consists of 11,788 images from 200 bird classes. Following [2]}, we randomly split categories into 100 classes for training, 50 for validation and 50 for evaluation. Our split is identical to  [3]} (discussion of class splits can be found in SM Sec. ). Prior work on this benchmark pre-processes the data in different ways: [2]} uses raw images as input, while [5]}, [6]} crop each image to a human-annotated bounding box.
We experiment on both settings for fair comparison.
<TABLE><TABLE>